Objectives of quality control in metal casting industries
The aims and objectives of foundry quality control are to improve the casting industries income by making the product more acceptable to the customers by providing long life, greater usefulness, versatility, aesthetic concepts, maintain ability tore duce company’s cost through reduction of losses due to the defects to achieve less scrap, less rework, less sorting and few erro turns from the customers [3]. In large scale captive foundries, quality control should help to optimum quality at the minimum
price, to make inspection prompt, to ensure quality control at proper stages to ensure production of non-defective cast products [8–10]. Another important aspect of quality control is judging the conformity of the process by the established standard sand taking suitable action when there are any deviation sob served. Its critical aim is to improve he quality and productivity by process control, experimentation and from the customer’s feed back. This assists for developing quality consciousness in the engineering concerns [4]. The quality control concept has three major attributes. They are: quality control is a form of participative management, quality control is a human resource development technique and quality control is a problem solving technique [11]. The basic organization structure of a quality circle should be effectively designed and hierarched for its efficient performance. The structure of quality control may vary from foundry to foundry, but it is useful to have a basic framework as a model. A quality circle will have a top-level steering committee and it will be coordinated by a coordinator through quality control facilitators. The facilitators are further supported by circle leader and circle members [12,13].
Quality and process control in foundries
Quality control is concerned with variation of a process or product characteristic about some hypothetical standard state. In assessing the significance of deviations from this state, distinction must be drawn between variations due to chance and those
resulting from definite changes in production conditions and requiring corrective action [7]. Control charts are provided with limits designed to show when these conditions are reached, the limits being established by statistical methods which take into account the natural vibrations arising in process and product. These methods also give guidance in the use of sampling techniques to minimize the task of measurement [14,15]. A limited amount of information concerning variation is given by simple
classify cation into categories, for example acceptance or ejection on inspection. Much more information can be derived, however, from measurement of some property which can be presented by a quantitative index, for example a linear dimension, temperature, composition or mechanical property. Collection of such data how the full nature of the variation and enables trends to be detected before a critical condition is reached. The spread of measurements obtained when a large number of minor causes combine to produce variations about some peak value is often characterized by the normal or Gaussian frequency distribution curve [7]. Once the particular Gaussian distribution characteristic of the process is known; therefore, this provides the means of finding whether any further set of readings confirms to the distribution and hence whether the process is operating under control [7]. The particular Gaussian distribution obtained under stable conditions illustrates the inherent variability of the process, or ‘process capability’. Since it represents the normal or chance variation when the process is operating satisfactorily, it should govern the choice of the process in relation to specification requirements; it is necessary to know not only that a casting can be made, but it can be made with a high probability of success. Control charts are designed to facilitate continuous observation of the magnitude and spread of measured values and to detect changes in either respect indicating that production is deviating from its characteristic stable state. Control charts for average and range are particularly applicable to the control of metal composition by analysis, to sand testing and to the dimensional inspection of castings where precision is of maximum importance [7]
The aims and objectives of foundry quality control are to improve the casting industries income by making the product more acceptable to the customers by providing long life, greater usefulness, versatility, aesthetic concepts, maintain ability tore duce company’s cost through reduction of losses due to the defects to achieve less scrap, less rework, less sorting and few erro turns from the customers [3]. In large scale captive foundries, quality control should help to optimum quality at the minimum
price, to make inspection prompt, to ensure quality control at proper stages to ensure production of non-defective cast products [8–10]. Another important aspect of quality control is judging the conformity of the process by the established standard sand taking suitable action when there are any deviation sob served. Its critical aim is to improve he quality and productivity by process control, experimentation and from the customer’s feed back. This assists for developing quality consciousness in the engineering concerns [4]. The quality control concept has three major attributes. They are: quality control is a form of participative management, quality control is a human resource development technique and quality control is a problem solving technique [11]. The basic organization structure of a quality circle should be effectively designed and hierarched for its efficient performance. The structure of quality control may vary from foundry to foundry, but it is useful to have a basic framework as a model. A quality circle will have a top-level steering committee and it will be coordinated by a coordinator through quality control facilitators. The facilitators are further supported by circle leader and circle members [12,13].
Quality and process control in foundries
Quality control is concerned with variation of a process or product characteristic about some hypothetical standard state. In assessing the significance of deviations from this state, distinction must be drawn between variations due to chance and those
resulting from definite changes in production conditions and requiring corrective action [7]. Control charts are provided with limits designed to show when these conditions are reached, the limits being established by statistical methods which take into account the natural vibrations arising in process and product. These methods also give guidance in the use of sampling techniques to minimize the task of measurement [14,15]. A limited amount of information concerning variation is given by simple
classify cation into categories, for example acceptance or ejection on inspection. Much more information can be derived, however, from measurement of some property which can be presented by a quantitative index, for example a linear dimension, temperature, composition or mechanical property. Collection of such data how the full nature of the variation and enables trends to be detected before a critical condition is reached. The spread of measurements obtained when a large number of minor causes combine to produce variations about some peak value is often characterized by the normal or Gaussian frequency distribution curve [7]. Once the particular Gaussian distribution characteristic of the process is known; therefore, this provides the means of finding whether any further set of readings confirms to the distribution and hence whether the process is operating under control [7]. The particular Gaussian distribution obtained under stable conditions illustrates the inherent variability of the process, or ‘process capability’. Since it represents the normal or chance variation when the process is operating satisfactorily, it should govern the choice of the process in relation to specification requirements; it is necessary to know not only that a casting can be made, but it can be made with a high probability of success. Control charts are designed to facilitate continuous observation of the magnitude and spread of measured values and to detect changes in either respect indicating that production is deviating from its characteristic stable state. Control charts for average and range are particularly applicable to the control of metal composition by analysis, to sand testing and to the dimensional inspection of castings where precision is of maximum importance [7]
